Idiopathic pulmonary fibrosis (IPF) is a chronic progressive disease that kills 40,000 Americans annually. The disease is characterized by a derangement of the lung stroma, ultimately resulting in respiratory failure due to proliferation of lung fibroblasts and accumulation of their extracellular matrix (ECM) products. This leads to obliteration of alveolar air spaces. The IPF lung fibroblast has lost key negative control mechanisms of its trophic signaling axis. This leads to genome-wide changes in ribosome recruitment to genes governing proliferation and other key cell functions. What is not known is how much of this aberrant genome-wide translation is due to abnormalities that are inherent to the fibroblasts, how much is due to the pathological ECM on which they reside and how much requires both. Here we propose to answer this question by utilizing an experimental system that closely simulates that in vivo environment: decellularized human lung tissue. We will adopt a genome-wide, systems biology approach to examining the pathobiology of the IPF fibroblast in a fibrotic microenvironment at a level that is known to be altered in IPF-ribosome recruitment. By comparing genome-wide expression patterns in primary lung fibroblasts derived from IPF and control patients on decellularized IPF and control lung slices, we are positioned to determine the relative importance of the cell-origin and the ECM-origin to the disease phenotype. Data will be generated using a combined polyribosome/RNA-Seq procedure. This translational data set will be used to generate a mathematical model of RNA regulatory element activity that can be used to understand the post-transcriptional processes that underlie the disease. Our central hypothesis is that IPF ECM can reprogram fibroblasts. We further posit that this reprogramming will manifest as highly organized changes in ribosome recruitment and that a mathematical model of these changes will pinpoint disease-defining pathology in the ECM-driven IPF signaling circuitry. Our specific aim is to use a genome-wide approach to characterize lung fibroblast gene expression (IPF and control) on decellularized lung ECM (IPF and control) and identify genes whose ribosome recruitment differs based on cell type, ECM type, cell and ECM type; and genes that are invariant across all conditions.